Future Research Topics

With my students, I am planning to venture into some more exciting fields of research. The following would be some of the topics where we can extend our AI Machine Learning techniques. You are most welcome to join us in our research!

Drone flying

Drones are becoming popular as gaming and entertainment object. However, they have potentially important business and social applications. Most users play with their drones by remotely controlling their flights. In the fully developed business ventures of the future, these drones should be able to plan their own flight paths and reach the destination without hitting any obstacles in the flight path. The obstacle avoidance Machine Learning algorithms for ground vehicle driving that we have developed in our laboratory can be used to "drone flying learning" with some minor modifications.

Brain and emotions

Some of my research collaborators collect a lot of brain scanned images of musicians while they are performing. Finer analysis of the brain scanned images can reveal the associations between the music genre and human emotions.

High definition image recognition

Our Convolutional Neural Networks are routinely learning to identify and classify images. However, even when executed on a high-spec Nvidia P100 GPU, they take several days to accomplish the learning task. The execution time will increase enormously when dealing with high definition images. We need to design new Neural Network structures to handle the identification and classification of high definition images.

Computational linguistics

While automatic machine translation is a still distant reality, researches have achieved success in producing small, but working linguistic models. Our preliminary Machine Learning models have produced satisfactory results on English and Spanish corpuses. We are planning to extend the models to other languages.

Multi-objective Optimization in higher dimensions

Our meta-heuristic optimization algorithms have demonstrated their robustness, and at the same time, flexibility and scalability in diverse domains like education, entertainment, healthcare, logistics, business, and so on. However, the maximum number of simultaneously optimized objective functions has been limited to two. We need to extend our know-how to optimize more than two objective functions that present themselves in the real-world optimization scenario.